Digital Commons Network^™

Leveraging Machine Learning For Traffic Congestion Management In Smart Cities, Omar Alhasai

Theses

Traffic congestion continues to be a major urban issue, leading to traffic delays, higher fuel costs, and air pollution problems. Traffic management systems currently function in reactive mode because their algorithms only operate following congestion development rather than preventing it. Smart cities need predictive systems based on data analytics and machine learning to actively control urban traffic movements because traffic continues to rise as a result of urbanization and population growth. The proposed research designs a machine learning–driven traffic congestion prediction system that uses genuine data obtained from Aarhus, Denmark, and METR-LA, Los Angeles. The study will analyze fundamental traffic …

Wegmans School Of Health And Nutrition’S Culinary Kitchen Cart Manual Development, Neena Bhala

Theses

To facilitate the initiation of culinary medicine at RIT, a manual to guide the use of a mobile kitchen cart was developed and evaluated. This manual was developed to support faculty, staff, and students’ use of a Mobile Kitchen Cart to be able to support culinary medicine and nutrition education activities. The Manual was directed to RIT faculty, staff, and students who have experience with the cart or intend to have future use with the cart. A qualitative evaluation study was conducted with ten participants including RIT faculty (n=2), students (n=4), and staff (n=4). Feedback on the manual was obtained …

A Comparative Study Of Inference-Time Scaling Strategies For Large Language Models, Oluwamayowa Owolabi

Theses

Large language models (LLMs) have demonstrated strong performance on a range of reasoning tasks, however, their reliability often depends not only on model size or training data, but also on inference-time strategies. However, existing inference-time methods are typically evaluated in isolation and under differing experimental assumptions, making it difficult to draw systematic conclusions about their relative effectiveness. This thesis proposes a controlled empirical study of inference-time scaling strategies for large language models under fixed inference-time compute budgets. The findings reveal that no single strategy dominates uniformly. PRM guided selection with the IBM Granite verifier achieves the highest absolute accuracy across …

Software Vulnerability Recidivism In Open-Source Projects, Brandon Keller

Theses

Software vulnerabilities present a major threat to businesses and individuals alike and it is therefore critical that a culture exists among software engineers to encourage the discovery and patching of security flaws. Vulnerability counts are a common way of evaluating a project’s security. However, this metric can run counter to building a developer culture of fault recognition if more vulnerabilities is always seen as a bad thing. While these counts can present a rough idea of a project’s history with security, they provide no insight into how the development team improves and learns as a result of a vulnerability. A …

Under The Surface: A Scalable Experiential Framework For Accessible Design Archives, Lo Fasano

Theses

Preserving design history is usually done by hiding it away. While institutions like the Vignelli Center for Design Studies house over 750,000 artifacts, the vast majority remain in restricted storage, with minimal space dedicated to displaying process materials alongside canonical final works. Digital archives document portions of these collections, but typically present them as static image galleries, leaving the evolutionary logic of a design, and the human labor behind it, invisible to the public. Under the Surface is a scalable, interactive framework designed to bridge archival preservation and public discovery. By transforming preserved artifacts into real-time digital experiences, the project …

Optimizing Urban Commute Quality Through Traffic Congestion Analysis And Predictive Modeling, Obaid Almansoori

Theses

Urban traffic congestion imposes significant economic, environmental, and social costs on rapidly growing cities worldwide. This research investigates how predictive analytics and machine  learning can be leveraged to classify and forecast traffic congestion severity in real time,  enabling data-driven decision-making for transportation planning, signal optimization, and  congestion management. A real-world traffic monitoring dataset comprising 5,952 observations collected over two months via  computer vision sensors at an urban intersection was analysed under the CRISP-DM frame- work. The  dataset records counts of four vehicle classes including cars, bikes, buses, and trucks at  15-minute intervals, alongside temporal variables such as time of day, …

Adapting Specpt For Hst Grism Spectroscopy Via Transfer Learning, Clive Kalathoor Binu

Theses

This thesis demonstrates the successful application of transfer learning to bridge ground-based and space-based spectroscopic analysis through adapting SpecPT (Spectroscopy Pre-trained Transformer) for Hubble Space Telescope WFC3 grism data for redshift prediction. Originally trained on high-resolution DESI spectra, SpecPT initially failed when applied directly to low-resolution, noisy HST WFC3 grism observations (Normalized Median Absolute Deviation (NMAD) = 0.2095, catastrophic outlier fraction ($\eta$) = 47.97\%). Through transfer learning on 8,530 high-quality 3D-HST spectra with emission-line SNR > 2.5 and z < 1.7, the model achieved substantial improvement (NMAD = 0.0724, $\eta$ = 26.69\%), representing a 65\% reduction in typical redshift error and 46\% decrease in catastrophic failures. The research addresses two primary objectives: establishing transfer learning effectiveness for cross-domain spectroscopic analysis and investigating whether supplementing grism spectra with broadband photometric data enhances performance. Counterintuitively, integrating comprehensive multi-wavelength photometric data from CANDELS significantly degraded performance (NMAD = 0.1641, $\eta$ = 36.51\%), challenging conventional astronomical assumptions about multi-modal data fusion and revealing critical failure modes in astronomical machine learning. This work establishes a unified framework for automated analysis of both ground-based and space-based spectroscopic surveys, with important implications for JWST, Euclid, and the Nancy Grace Roman Space Telescope. The demonstrated capability to adapt models across instrumental domains provides a scalable approach for processing large data volumes from next-generation missions, validating foundational model approaches that can be developed once and efficiently adapted across diverse observational contexts.

In-Context Retrieval For Molecules And Chemical Synthesis Pathways, Abhisek Dey

Theses

Contrastive learning methods require well-defined positive pairs, limiting their applicability to domains where complete, high-fidelity pairings are available. In practice, large-scale scientific corpora --including patents, publications, and web-scale data -- contain vast quantities of contextually relevant but incompletely paired samples that are discarded under standard training paradigms. In this work, we demonstrate that hard negative mining can be leveraged to construct pseudo-positive supervision signals from unpaired or partially paired data, enabling contrastive learning to exploit the full breadth of available corpora without sacrificing representational quality. Using a large-scale chemical drug patent corpus as a testbed, we train a cross-modal contrastive …

Toward Reliable Computational Social Science: Inconsistency-Aware Methods For Human Annotation And Ai Inference, Sujan Dutta

Theses

As artificial intelligence (AI) becomes increasingly common in computational social science, \textit{inconsistency} has emerged as a key challenge. AI models often contradict themselves when given equivalent inputs, disagree with other models on the same data, and diverge from human judgments in seemingly opaque ways. Human annotators exhibit their own inconsistencies, both within individuals and across groups shaped by differing values and identities. Rather than treating these inconsistencies simply as noise, this dissertation argues that they contain meaningful signals that can be leveraged to improve learning efficiency, strengthen evaluation, and increase the reliability of large-scale social measurement. To study this phenomenon, …

Beyond The Launch: Designing Integrated Marketing Communications Across The Publishing Lifecycle, Philip J. Boutin Jr.

AMTP Proceedings 2026

This paper advances a lifecycle view of integrated marketing communications for book publishing and specifies a practical model beyond launch. We present the Lifecycle IMC in Publishing (L-IMC) framework with four layers—strategic capability, orchestration, phased execution (pre-launch, launch, post-publication), and measurement/learning—grounded in evidence on carryover, cross-media complementarity, discoverability, and the creator economy. Seven propositions predict that lifecycle consistency, coordinated post-publication activity, metadata priming, creator–title fit with clear disclosures, network-aware seeding, continuous testing, and reserved reinforcement budgets improve visibility, conversion, and returns. Design principles include codified message architecture and governance, a vetted creator bench, managed discoverability, sequencing high-trust signals before conversion …

Department Of Politics And Government News And Views, Spring 2026, Department Of Politics And Government, Illinois State University

Department of Politics and Government News and Views

Newsletter of the Department of Politics and Government at Illinois State University

Evaluating The Role Of Social Media And Consumer Preferences In The Food Truck Industry, David Farabaugh, Kayla Weslager, Noah Kohan, Anthony George

AMTP Proceedings 2026

This study examines how a mobile food business, specifically a local food truck operating throughout Cambria County, Pennsylvania, can use market insights and strategic marketing to attract new customers and maintain a loyal following. As food trucks continue to grow in popularity and competition increases, offering good food alone is no longer enough to stand out. Instead, success often depends on delivering a memorable overall experience, including efficient service, convenience, brand personality, and consistent customer engagement. Using the featured food truck as a case example, this research analyzes customer preferences, travel patterns, and the influence of social media platforms such …

Pivot: Plan For Institutional Vitality And Organizational Transformation, 2025-2026 Report, Office Of Academic Affairs, Research And Graduate Studies, Richard Tankersley, Shelly Chabon

Office of Academic Affairs Publications

This report documents the conduct and results of PIVOT's first review cycle, from its September 2025 launch through the submission of recommendations to President Ann Cudd on February 23, 2026. Track 1 reviewed 293 academic programs, each by three to five academic leaders, with calibration by the Deans' Council and feedback from units before classifications were finalized. Resulting classifications were 25 Grow, 85 Sustain, 112 Revitalize, and 71 Sunset. Track 2 reviewed 163 units through a Core Review Team, producing 7 Invest, 61 Sustain, 54 Reassess, 28 Restructure/Consolidate, and 13 Phase Out classifications. The report presents financial modeling projecting approximately …

Use Of Inverse Probability Weighting In Cardiovascular Surgical Outcomes Research: Principles, Limitations, And Recommendations, Zhongjian Liu, Wei-Guo Ma, Lei Liu, Prashanth Vallabhajosyula, Haibo Wang

2020-Current year OA Pubs

This statistical primer presents a comprehensive introduction to the use of inverse probability of treatment weighting (IPTW), a method for rebalancing group confounders at baseline in cardiovascular surgical outcomes research. We leveraged a retrospective study comparing the outcomes of 2 different surgical approaches to aortic arch pathology to illustrate the essential aspects of performing IPTW, including basic theories, application, extreme weights, underestimated variance, heterogeneity of treatment effect, and multicollinearity. The limitations of IPTW were discussed with examples of solutions. Ten practical recommendations are made on avoiding the pitfalls in the use of IPTW. Proper use of IPTW may effectively reduce …

Ten Tips On How To Prevent And Manage Post-Transplant Lymphoproliferative Disease In Kidney Transplant Recipients, Rose Mary Attieh, Armin Ghobadi, Naoka Murakami

2020-Current year OA Pubs

Post-transplant lymphoproliferative disease (PTLD) remains a challenging and high-impact complication of kidney transplantation, requiring thoughtful prevention, timely recognition, and multidisciplinary management. Key strategies include careful selection of immunosuppressive regimens, particularly avoiding belatacept in Epstein-Barr virus (EBV)-seronegative recipients and exercising caution with lymphodepleting induction in EBV-mismatched pairs, along with targeted EBV surveillance in high-risk patients. Once PTLD is suspected or confirmed, accurate staging and a stepwise treatment approach beginning with reduction of immunosuppression and escalating to rituximab, chemotherapy, or advanced cellular therapies are essential, with EBV-CTLs and chimeric antigen receptor T-cell therapy offering promising options in refractory disease. Close monitoring for …

Ethical Controversies In Organ Procurement: A National Survey On Public Perceptions Of Thoracoabdominal Normothermic Regional Perfusion, Trevor M Bibler, Jill Oliver Robinson, Adam Omelianchuk, Tariq Nisar, Savitri Fedson, Ariel N Levchenko, Amy L Mcguire

Center for Medical Ethics and Health Policy Staff Publications

Thoracoabdominal normothermic regional perfusion (TA-NRP) would likely expand the quantity and quality of organs procured after controlled circulatory death donation in the United States, yet its ethical permissibility remains contested. We surveyed a representative sample of US adults (n = 975) with the goal of assessing their perspectives on the ethical permissibility of TA-NRP. After reading a neutral description of TA-NRP, participants judged its permissibility, reviewed 5 critic and 5 supporter arguments (in random order), and chose which argument they found most convincing. Multivariable logistic regression examined predictors of agreeing with critics. Before exposure to the arguments, 51.5% stated that …

Sustainability In Concrete: Decision-Makers, Dismissal Points, And A Framework For Implementation, Max Dennison

Construction Management

Concrete is essential to modern infrastructure, but is also one of the largest sources of embodied carbon, with cement production alone responsible for a significant share of global CO₂ emissions. Although low-carbon and otherwise “sustainable” concrete technologies are growing, their use in everyday projects remains limited. This research investigates why sustainable concrete options are most often dismissed during the project lifecycle, who drives these decisions, and what conditions are needed to enable broader adoption. Using a combination of literature review and semi-structured interviews with professionals in contracting, life-cycle assessment, sustainability consulting, and materials production, the study maps decision points from …

Body Mass Index And Survival In Children Receiving Extracorporeal Membrane Oxygenation, Pilar Anton-Martin, Keith Baxelbaum, Shilpa Vellore, Erika O'Neil, Vinai Modem, Sameer Thadani

Faculty, Staff and Students Publications

Importance: Underweight and obesity represent opposite ends of the nutritional risk spectrum that negatively affect children's health worldwide. Both conditions have been associated with increased mortality in pediatric patients receiving extracorporeal membrane oxygenation (ECMO) support.

Objective: To investigate the association of underweight and obesity status with pediatric ECMO outcomes using body mass index (BMI) z scores.

Design, setting, and participants: This retrospective cohort analysis used data from the Extracorporeal Life Support Organization (ELSO) database from January 1, 2019, to December 31, 2023. Participants included all pediatric patients from international ECMO centers aged 29 days to 18 years who received ECMO …

Development And Internal Validation Of A Pretransplant Biomarker Panel For Mortality Prediction Following Liver Transplant, Guergana G Panayotova, Sopio Simonishvili, Lianhua Jin, Duc T Nguyen, Edward A Graviss, Yong Qin, Anastasia Xynogala, Tumininu Ayorinde, Laurie J Minze, Alexander Lemenze, Krupa R Mysore, Julie M Corkrean, Linda W Moore, Flavio Paterno, Ashish Saharia, Constance M Mobley, Arpit Amin, Mark J Hobeika, Xian C Li, Paul J Gaglio, R Mark Ghobrial, James V Guarrera, Keri E Lunsford

Faculty, Staff and Students Publications

Importance: Current pretransplant clinical scoring systems fail to accurately estimate post-liver transplant (LT) survival, making recipient selection challenging. Persistent immune dysfunction contributes to early LT recipient mortality but is not captured by existing models.

Objective: To identify plasma biomarkers of pretransplant immune dysfunction and to develop a biomarker-based pre-LT risk stratification tool to predict post-LT mortality.

Design, setting, and participants: Prospective biomarker analysis of consecutively enrolled adult LT recipients was conducted. Healthy controls were included for baseline comparison. Patients undergoing LT at Houston Methodist Hospital (October 1, 2013, to December 31, 2017) and Rutgers/University Hospital (January 1, 2019, to March …

Advanced Artificial Intelligence Vs Simpler Models For 1-Year Death Prediction Among Patients Receiving Hemodialysis, Karthikeyan K, Jennifer E Flythe, Patrick H Pun, Wolfgang C Winkelmayer, David Carlson

Faculty, Staff and Students Publications

Objectives: We evaluated the data requirement for modern AI tools to outperform simpler models in predicting short-term mortality in over 500 000 patients with hemodialysis-dependent kidney failure.

Materials and methods: We compared logistic regression, boosting, and transformers using increasingly complex feature sets (from last-visit data to full trajectories). Performance was measured using the area under the ROC curve (AUC-ROC) and the Precision-Recall curve (AUC-PR) across training data sizes ranging from 500 to 490 197 samples.

Results: Using features with temporal information is beneficial across all models. On the full dataset, Transformers (AUC-ROC = 0.8568) and boosting (AUC-ROC = 0.8598) perform …

The International Pediatric Headache Didactic Series: A Novel Curriculum Innovation, Sara Pavitt, Sruthi Ilangovan, Zoë Allen, Samantha L Irwin, Irene Patniyot

Faculty, Staff and Students Publications

Objectives: The International Pediatric Headache Didactic Series (IPHDS) was developed to provide free, comprehensive pediatric headache education to healthcare professionals worldwide. The objective of this study was to describe the design, implementation, and impact of this prospective educational intervention.

Background: Headache is the most common neurological symptom within the pediatric population. Yet, only nine fellowships are offered in pediatric headache medicine. Limitations in access to education and training are often cited as reasons for diagnostic and management barriers. To address this gap, the IPHDS was established in July 2022.

Methods: IPHDS is a recurring series consisting of 23 biweekly lectures. …

Aht Diagnoses: The Influences Of Clinical Presentation And Evidence Of Impact, Ruairi Smith-Dewey, Angela Bachim, Colleen Bressler, Kristine Campbell, Lori Frasier, Christopher Greeley, Danielle Horton, Nicole Johnson, Jan Leonard, Megan M Letson, Caitlin Mcnamara, Ashley Sherman, Shalon Nienow, Stuart Sommers, Joanne N Wood, James Anderst

Faculty, Staff and Students Publications

Background: The frequency of abusive head trauma (AHT) diagnoses by child abuse pediatricians (CAPs), especially regarding external evidence of head impact, has been questioned.

Objectives: To compare CAP diagnoses in subjects with subdural hemorrhage (SDH) across clinical presentations, including subgroups with and without external evidence of head impact. Additionally, we aimed to describe subjects with SDH and concomitant suspicious injuries (CSI) without evidence of head impact.

Participants and setting: Multicenter retrospective study including subjects < 24 months old with SDH.

Methods: Subjects were divided into groups based on clinical presentations: Ill SDH only, Non-ill SDH only, and SDH + CSI. Groups were subcategorized based on presence/absence …

Confessions In Cases Of Child Physical Abuse-A Capnet Study, Margaret R Russell, Antoinette L Laskey, Henry T Puls, Suzanne P Starling, Joanne N Wood, Daniel M Lindberg, Nancy S Harper, Caitlin R Mcnamara, Angela N Bachim, Farah W Brink, Lori D Frasier, James D Anderst, Porcia Vaughn, Kristine A Campbell

Faculty, Staff and Students Publications

Objective: Prior research on confessions of physical abuse (PA) has explored mechanisms of injury. Little is known about conditions supporting a confession of abuse or how confessions may influence case outcomes.

Methods: This cross-sectional study of suspected PA in children aged < 10 years at 10 centers participating in CAPNET, a multicenter child PA research network, included children with in-person Child Abuse Pediatrics (CAP) consultations between February 2021 and December 2022 and excluded children without injury. Our focus was a confession of inflicted injury known to the CAP during clinical involvement. We compared child and clinical characteristics, out-of-home (OOH) placements, and arrests between cases with and without confessions. Multivariable models using generalized estimating equations (GEE) produced adjusted predicted probabilities (APP) clustering by CAPNET site.

Results: Confessions were known to CAPs in 115/4297 (2.7%) cases, with significant site variability. In a multivariable GEE model, confessions were more likely in cases with injuries with high specificity for abuse (APP 6.0% vs 1.6%, P < .001), near-fatality (APP 5.6% vs 2.3%, P < .001), and older children (APP 4.8% vs 2.5%, P = .025). OOH placements and arrests were more common in cases with confessions. CAP awareness of confessions, OOH placements, and arrests did not follow racial or ethnic patterns seen in the US child welfare system. Lower socioeconomic status was associated with OOH placements and arrests but not with CAP awareness of confessions.

Conclusions: Our findings highlight differences in case characteristics and outcomes where a confession is known to the CAP and raise questions about …

Fronto-Cerebellar Features Associate With Cognitive Dysfunction In Childhood-Onset Systemic Lupus Erythematosus, Hanne Van Der Heijden, Gabrielle Alonzi, Amanda Cao, Raquel Van Gool, Merve Koç Yekedüz, Lise Vrolix, Itamar Ronen, Vanessa Rameh, Kyle Mcbrearty, Aditi Deokar, Robert P Sundel, Eyal Muscal, Joseph Gonzalez-Heydrich, Andrea Knight, Joyce C Chang, Jaymin Upadhyay

Faculty, Staff and Students Publications

Objective: Cognitive dysfunction (CD) is a prevalent symptom in childhood-onset systemic lupus erythematosus (cSLE). This study aimed to investigate the neurobehavioral basis of CD in cSLE.

Methods: Patients with cSLE (N=20) and age- and sex-matched healthy controls (HCs, N=20) completed questionnaires and multiple neurocognitive tests. The Systemic Lupus Erythematosus Disease Activity Index 2000 and laboratory markers were used to monitor patients' clinical status. Neuroimaging assessments included functional near-infrared spectroscopy (fNIRS), functional magnetic resonance imaging (fMRI), and structural MRI.

Results: cSLE patients demonstrated moderate disease activity with high inflammation and immune dysregulation, alongside low medication adherence. Relative to HCs, cSLE patients …

Trauma-Related Compulsions In Obsessive-Compulsive Disorder: Functional Insights From Factor Analysis, Caitlin M Pinciotti, Max Thorsson, Gregor Horvath, Matti Cervin

Faculty, Staff and Students Publications

Resisting obsessive-compulsive disorder (OCD) compulsions is a key predictor of exposure and response prevention (ERP) effectiveness, yet trauma-exposed individuals with OCD endorse more severe compulsions and are more likely to be labelled 'treatment resistant.' Among trauma-exposed individuals, compulsions are theorised to function to prevent future trauma and cope with trauma-related responses. Recent findings suggest that certain compulsions in the context of trauma exposure differentially impact treatment outcomes, yet missing from extant literature is a larger empirically derived conceptualisation for how trauma may impact the underlying function of compulsions. In a sample of 662 adult patients enroled in intensive OCD treatment …

Robotic Single-Incision Laparoscopic Surgery For The Management Of Endometriosis: First Experience Via The Da Vinci Sp Platform, Qiannan Yang, Daniel Y Lovell, Xiaoming Guan

Faculty, Staff and Students Publications

Objective: To demonstrate the feasibility and mid-term outcomes of Robotic single-port single-incision laparoscopic surgery (RSP-SILS) for endometriosis management.

Methods: A retrospective analysis was conducted on 50 adult women with endometriosis who underwent RSP-SILS via the da Vinci SP platform between November 2023 and July 2025.

Results: Median total operative time was 142 min, robot dock time was 3 min, and robot console time was 99 min. Median estimated blood loss was 25 mL. No conversion occurred. Reported mid-term outcomes included 1 case each of pelvic haematoma, Clostridioides difficile colitis, and umbilical surgical site infection, as well as 3 cases of …

Robotic-Assisted Transumbilical Single-Site And Transvaginal Notes Resection Of Abdominal Wall Cesarean Scar Endometriosis: Two Case Reports, Xiaoming Guan, Qiannan Yang, Victoria Zhang, Chunhua Zhang

Faculty, Staff and Students Publications

No abstract provided.

A Comprehensive Review Of Tear Fluid Proteome Alterations In Dry Eye Disease: Insights Into Pathophysiology And Biomarker Potential, Saleh Ahmed, Steven Safille, Victoria Clifton, Shruti Sharma, Cintia S De Paiva, Ashok Sharma

Faculty, Staff and Students Publications

Tear fluid is a highly specialized and dynamic biofluid composed of proteins, lipids, mucins, and electrolytes that is essential for maintaining ocular surface integrity, immune defense, and tear film stability. Growing evidence from tear proteomic studieshas revealed extensive alterations in protein composition in dry eye disease (DED), reflecting a complex interplay between local ocular surface pathology and systemic inflammatory influences. This review summarizes proteomic findings from 50 published studies to identify tear proteins that are consistently upregulated or downregulated in DED and to interpret their biological relevance in the context of ocular surface homeostasis. Across studies, proteins upregulated in DED …

Rexinoid Net-3ib Promotes Resident Macrophage Gene Expression And Mitigates Desiccation-Induced Ocular Surface Disease, Jehan Alam, Yangluowa Qu, Jianming Shao, Ebru Yaman, Karen Zheng, Hiroki Kakuta, Stephen C Pflugfelder

Faculty, Staff and Students Publications

Purpose: To evaluate the effects of rexinoid NEt-3IB on desiccating stress-induced dry eye, as well as monocyte/macrophage gene expression and cellular trajectory.

Methods: Eyes were topically treated with rexinoid NEt-3IB (5 µM) or vehicle three times a day for 5 days of desiccating stress-induced dry eye. Single-cell RNA sequencing (RNA-seq) profiled gene expression in conjunctival immune cells. RNA-seq was also used to evaluate gene expression in lipopolysaccharide (LPS)-stimulated, dexamethasone-treated (Dex, 1 µM), or NEt-3IB-treated (1-1000 nM) cultured monocytes. Cellular state trajectory and latent time were inferred with scVelo, and latent-time-associated genes were identified using Monocle 3. Permeability to Oregon Green-labeled …

Kidney Disease And Heart Failure: Recent Advances And Current Challenges: Conclusions From A Kidney Disease: Improving Global Outcomes (Kdigo) Controversies Conference, Carolyn S P Lam, Biykem Bozkurt, David Z I Cherney, Justin A Ezekowitz, Meg J Jardine, Sadiya S Khan, Magdalena Madero, Mark J Sarnak, Jozine M Ter Maaten, Michael Cheung, Jennifer M King, Morgan E Grams, Michel Jadoul, Nisha Bansal

Faculty, Staff and Students Publications

Heart failure (HF) and chronic kidney disease (CKD) frequently coexist, which elevates the risks of hospitalization, disease progression, and death. Despite advances in treating each condition independently, many challenges remain in diagnosing and managing them in combination. In March 2024, Kidney Disease: Improving Global Outcomes (KDIGO) held the Controversies Conference on Kidney Disease and Heart Failure: Recent Advances and Current Challenges. Discussions highlighted the complex, bidirectional relationship between HF and CKD, including shared risk factors and overlapping pathophysiology as well as nuances in interpreting biomarkers such as natriuretic peptides and serum creatinine. Sodium-glucose cotransporter-2 inhibitors, renin-angiotensin-aldosterone system inhibitors, and emerging …